Player density based region division for regional chat

ABSTRACT

The virtual location of a player in a location-based game is determined from the real-world location of the player&#39;s client device. The location-based game provides the player access to one or more chat room based on their location. To determine the locations of chat room, a server analyzes player locations in a geographic region, clusters player locations to identify centroids, and adjusts the clusters based on constraints. The server selects chat room locations (e.g., at points of interest) to more evenly balance the number of players in each chat room while complying with one or more restraints on the size of the geographic area served by each chat room.

TECHNICAL FIELD

The present disclosure relates generally to location-based gaming and,in particular, to determining chat room locations in such games.

BACKGROUND

Location-based games use the real world as their geography. Parallelreality games are a type of location-based game that use a virtual worldthat parallels the real-world geography. Players can interact andperform various game objectives in the parallel virtual world bynavigating and performing actions in the real world. To communicatewithin the parallel reality game, players may converse in chat roomslocated throughout the virtual world. For example, a player may join onechat room to communicate with other players during a raid. However, ifthe player moves to a new location within the real world to participatein other virtual experiences with a different group of players, theoriginal chat room located near the raid would not be connected to otherplayers nearby in the real world who may be using other chat rooms. Inaddition, even if the player only moves a short distance away from theoriginal chat room, the virtual experiences and players nearby may bedifferent than those at the player's original location.

SUMMARY

In a location-based parallel reality game, players navigate a virtualworld by through the real world with a location-aware client device,such as a smartphone. As players navigate the virtual world toparticular in virtual experiences or interact with virtual elements,they may chat with one another via chat rooms strategically locatedwithin the virtual world. These chat rooms may be regionally placed inthe virtual world, such that they are located near geographic locationswith a large observed density of player locations. Chat rooms may alsobe located near points of interest within the parallel reality game,such as virtual elements or virtual experiences.

Many client devices used by players in the parallel reality game mayinclude positioning devices that track player location information asplayers move throughout the real world while playing the parallelreality game. In various embodiments, client devices send the playerlocation information to a server that hosts the parallel reality game.The game server determines chatroom locations based on the playerlocation information.

In one embodiment, the game server determines chat room locations for ageographic region by iteratively clustering the player locations withinthe geographic region into centroid areas, adjusting the clusters tomore evenly balance the number of players associated with each centroidarea while still dispersing the chat rooms in a way that accounts forthe natural groupings of players in the real world. Once the chat roomslocations have been determined, the game server may select chat roomsfor individual users based on their current location within the game andprovide messages from the chat rooms to the users.

These and other features, aspects and advantages may be betterunderstood with reference to the following description and appendedclaims. The accompanying drawings illustrate specific embodiments and,together with the description, serve to explain various principles.However, the drawings should not be considered limiting. Rather, thescope of protection should be determined from the claims.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a block diagram illustrating a networked computing environmentsuitable for operating a location-based game, according to oneembodiment.

FIG. 2 is block diagram of a client device shown in FIG. 1, according toone embodiment.

FIG. 3 is a block diagram of the game server shown in FIG. 1, accordingto one embodiment.

FIGS. 4A-4B are an example of player locations grouped into aggregatedpoints within a geographic region, which are used to further determinecentroids, according to one embodiment.

FIGS. 5A-5C illustrate centroids at various stages of a process fordetermining chat room locations, according to one embodiment.

FIG. 6 is an example of chat room locations with points of interestwithin a geographic region, according to one embodiment.

FIG. 7 is a flowchart depicting a method for providing messages from achat room to a user, according to one embodiment.

FIG. 8 is a flowchart depicting a method for determining chat roomlocations, according to one embodiment.

FIG. 9 is a flowchart depicting a method for grouping aggregated pointsinto centroids on a map, according to one embodiment.

FIG. 10 is a block diagram illustrating an example computer suitable foruse in the network computing environment of FIG. 1, according to oneembodiment.

DETAILED DESCRIPTION

The figures and the following description describe certain embodimentsby way of illustration only. One skilled in the art will readilyrecognize from the following description that alternative embodiments ofthe structures and methods may be employed without departing from theprinciples described. Reference will now be made to several embodiments,examples of which are illustrated in the accompanying figures. It isnoted that wherever practicable similar or like reference numbers areused in the figures to indicate similar or like functionality. Also,where similar elements are identified by a reference number followed bya letter, a reference to the number alone in the description thatfollows may refer to all such elements, any one such element, or anycombination of such elements.

Overview

Generally, the present disclosure relates to determining chat roomlocations for parallel reality games that occur in virtual worlds thatare mapped to real world locations.

A game server can host a location-based parallel reality game having aplayer gaming area that includes a virtual environment with a geographythat parallels at least a portion of the real-world geography. Playerscan navigate a virtual space in the virtual world by navigating acorresponding geographic space in the real world. In particular, playerscan navigate a range of coordinates defining a virtual space in thevirtual world by navigating a range of geographic coordinates in thereal world.

In one aspect, the positions of players can be monitored or trackedusing, for instance, a positioning system (e.g. a GPS system) associatedwith a player's mobile computing device (e.g. a cell phone, smartphone,gaming device, or other device). As players move about in the realworld, player location information can be provided to the game serverhosting the parallel reality game over a network. The game server canupdate player locations in the parallel virtual world to correspond withthe player locations in the real world.

The parallel reality game can also include one or more points ofinterest that players can interact with during the course of theparallel reality game. Points of interest may include, but are notlimited to, virtual elements, virtual objects, virtual experiences, andthe like. Points of interest may also be located at virtual locationsthat correspond to the real-world locations of landmarks, stores,recreational areas, or other real-world features that may be of interestto players. To interact with points of interest, a player may travel tothe corresponding location of the point of interest in the real worldand select the point of interest in the parallel reality game.

As players navigate and interact with the virtual world, they maycommunicate with one another via chat rooms located throughout thevirtual world. When a player joins a chat rooms, they may send andreceive messages with other players in the chat room. Chat rooms may belocated at a subset of the points of interest. According to aspects ofthe present disclosure, chat room locations can be determined based onplayer location data gather by game player's client devices as theynavigate the virtual world. The data can be analyzed to determine chatroom locations that balance minimizing the average distance betweenplayer locations and the nearest chat rooms with equalizing the numberof players in each chat room.

In one embodiment, a game server associated with a parallel reality gamecan access data associated with the location of individuals in the realworld. The data associated with the location of individuals in the realworld can be obtained or derived from any suitable source. The dataassociated with the location of individuals in the real world caninclude the real-world positions of mobile device associated with thoseindividuals. In particular, users of mobile devices, such as smartphones, can optionally provide position information, in terms ofgeographic location in the real world, in order to enhance certainlocation-based features or other functionality. Any informationoptionally provided by mobile device users can be provided on conditionsof anonymity to protect the privacy of the user optionally providing theposition information.

Data associated with the locations of individuals in the real world canalso include data associated with the locations of players of theparallel reality game. In particular, the game server can receive asnapshot of device position information at a given time from each clientdevice of players of the parallel reality game. The game server cananalyze the snapshot to determine locations of individuals in the realworld and generate chat room locations based on such data. The gameserver may use these chat rooms locations for a given period of time(e.g., a day, month, year, etc.) and may periodically update the chatroom locations using a new snapshot of player device information.

Exemplary Location-Based Parallel Reality Gaming System

Exemplary computer-implemented location-based gaming systems accordingto exemplary embodiments of the present disclosure will now be setforth. The present subject matter will be discussed with reference to aparallel reality game. A parallel reality game is a location-based gamehaving a virtual world geography that parallels at least a portion ofthe real-world geography such that player movement and actions in thereal-world affect actions in the virtual world and vice versa. Those ofordinary skill in the art, using the disclosures provided herein, shouldunderstand that the subject matter of the present disclosure is equallyapplicable to other gaming systems.

FIG. 1 illustrates an exemplary computer-implemented location-basedgaming system 100 configured in accordance with an embodiment. Thelocation-based gaming system 100 provides for the interaction of aplurality of players in a virtual world having a geography thatparallels the real world. In particular, a geographic area in the realworld can be linked or mapped directly to a corresponding area in thevirtual world. A player can move about in the virtual world by moving tovarious geographic locations in the real world. For instance, the system100 can track a player's position in the real world and update theplayer's position in the virtual world based on the player's currentposition in the real world. For example, a coordinate system in the realworld (e.g., longitude and latitude) may be mapped to a coordinatesystem in the virtual world (e.g., x/y coordinates, virtual longitudeand latitude, etc.).

In the embodiment shown in FIG. 1, the system 100 has a client-serverarchitecture, where a game server 110 communicates with one or moreclient devices 120 over a network 130. Although three client devices 120are illustrated in FIG. 1, any number of client devices 120 can beconnected to the game server 110 over the network 130. In otherembodiments, the distributed location-based gaming system 100 includesdifferent or additional elements. Furthermore, the functions may bedistributed among the elements in a different manner than described.

The game server 110 hosts a master state of the location-based game andprovides game status updates to players' client devices 120 (e.g., basedon actions taken by other players in the game, changes in real-worldconditions, changes in game state or condition, etc.). The game server110 receives and processes input from players in the location-basedgame. Players may be identified by a username or player ID (e.g., aunique number or alphanumeric string) that the players' client devices120 send to the game server 110 in conjunction with the players' inputs.

For example, the game server 110 may determine locations for chat roomsbased on a snapshot of device position information, which indicates amultitude of player locations in the real world. The game server 110breaks a geographic region of a map into cells (e.g., S-cells) andcreates aggregated points weighted by the number of player locationswithin each cell. The game server determines centroids using aclustering algorithm (e.g., an iterative k-means clustering algorithm)and iterative border adjustment. The game server determines chat roomlocations based on the centroids. The chat room locations may be pointsof interest on the map, such as monuments, stores, public buildings,sculptures, or other identifiable real-world locations. For each chatroom located within the virtual world, the game server 110 may selectand provide messages to players of the parallel reality game. Variousembodiments of the game server 110 are described in greater detailbelow, with reference to FIG. 3.

The client devices 120 are computing devices with which players caninteract with the game server 100. For instance, a client device 120 canbe a smartphone, portable gaming device, tablet, personal digitalassistant (PDA), cellular phone, navigation system, handheld GPS system,or other such device. A client device 120 may execute software (e.g., agaming application or app) to allow a player to interact with thevirtual world. A client device 120 may also include hardware, software,or both for providing a user interface for chat rooms. A user may chooseto join a chat room and send and receive messages via the userinterface. Various embodiments of client device 120 are described ingreater detail below, with reference to FIG. 2.

The network 130 can be any type of communications network, such as alocal area network (e.g. intranet), wide area network (e.g. Internet),or some combination thereof. The network can also include a directconnection between a client 120 and the game server 110. In general,communication between the game server 110 and a client 120 can becarried via a network interface using any type of wired and/or wirelessconnection, using a variety of communication protocols (e.g. TCP/IP,HTTP, S1v1TP, FTP), encodings or formats (e.g. HTML, JSON, XML), and/orprotection schemes (e.g. VPN, secure HTTP, SSL).

FIG. 2 is block diagram of a client device 120 shown in FIG. 1,according to one embodiment. Because the gaming system 100 is for alocation-based game, the client device 120 is preferably a portablecomputing device, such as a smartphone or other portable device, thatcan be easily carried or otherwise transported with a player. A playercan interact with the virtual world simply by carrying or transportingthe client device 120 in the actual world. The client device 120 caninclude a positioning device 210 that monitors the position of theclient device 120 in the real world. The positioning device 210 can beany device or circuitry for monitoring the position of the client 120.For example, the positioning device 210 can determine actual or relativeposition by using a satellite navigation positioning system (e.g. a GPSsystem, a Galileo positioning system, the Global Navigation satellitesystem (GLONASS), the BeiDou Satellite Navigation and Positioningsystem), an inertial navigation system, a dead reckoning system, basedon IP address, by using triangulation and/or proximity to cellulartowers or WiFi hotspots, and/or other suitable techniques fordetermining position.

As the player moves around with the client 120 in the real world, thepositioning device 210 tracks the position of the player's client device120 and provides the client device position information to the gamemodule 220. The game module 220 updates the player's location in thevirtual world based on coordinates of the position of the player'sclient device 120 in the real world. Thus, game module 220 maintains alocal state of the virtual world on the client device 120. The gamemodule 220 can provide player location information to the game server110 over the network 130 such that the game server 110 maintains a totalgame state with updated player locations and provides the game module220 with periodic updates so that the local game state can reflect thetotal game state.

The game module 220 communicates information about the virtual worldwith the user interface module 230. The user interface module 230 of theclient device 120 constructs and displays components of the userinterfaces of the client device 120. The user interface may displaydepictions of the virtual world to the user including components of thevirtual world, such as virtual elements and virtual experiences, asreceived from the game module 220. The user interface module 230 mayalso display chat room locations in the virtual world, as well asmessages sent between users in the chat rooms. A user may interact withthe client device 120 to engage with virtual elements, participate invirtual experiences, or converse in chat rooms. For example, the userinterface module 230 may display a view of the virtual world depictingpoints of interest, chat rooms, and other virtual experiences. The userof the client device 120 can interact with these components via the userinterface to complete a task, join a chat room, or participate in araid, among other actions.

The local data store 240 is one or more computer-readable mediaconfigured to store data used by the client device 120. For example, thelocal data store 240 may store the player location information trackedby the positioning device 210, a local copy of the current state of theparallel reality game, or any other appropriate data. Although the localdata store 240 is shown as a single entity, the data may be split acrossmultiple media. Furthermore, data may be stored elsewhere (e.g., in adistributed database) and accessed remotely via the network 130.

FIG. 3 illustrates one embodiment of the game server 110 suitable forhosting a location-based parallel-reality game. In the embodiment shown,the game server 110 includes a universal game module 310, a locatormodule 320, a chat room module 330, and a game database 340. In otherembodiments, the game server 110 contains different or additionalelements. In addition, the functions may be distributed among theelements in a different manner than described.

The game server 110 can be configured to receive requests for game datafrom one or more client devices 120 (for instance, via remote procedurecalls (RPCs)) and to respond to those requests via the network 130. Forinstance, the game server 110 can encode game data in one or more datafiles and provide the data files to a client device 120. In addition,the game server 110 can be configured to receive game data (e.g. playerlocation, player actions, player input, etc.) from one or more clientdevices 120 via the network 130. For instance, the client device 120 canbe configured to periodically send player input, player location, andother updates to the game server 110, which the game server 110 uses toupdate game data in the game database 340 to reflect changed conditionsfor the game. The game server 110 may also send game data to clientdevices 120, such as other player locations, chat room locations,virtual element locations.

The universal game module 310 hosts the location-based game for playersand acts as the authoritative source for the current status of thelocation-based game. The universal game module 310 receives game datafrom client devices 120 (e.g., player input, player location, playeractions, player status, landmark information, etc.) and incorporates thegame data received into the overall location-based game for all playersof the location-based game. With the game data, the universal gamemodule 310 stores a total game state of the game that can be sent to aclient device 120 to update the local games state in the game module220. The universal game module 310 can also manage the delivery of gamedata to the client devices 120 over the network 130.

The locator module 320 can be a part of or separate from the universalgame module 310. The locator module 320 is configured to access dataassociated with real world actions, analyze the data, and determinevirtual experiences in the virtual world based on the data associatedwith real world actions. For instance, the locator module 320 can modifygame data stored in the game database 340 to locate virtual experiencesin the virtual world based on the data associated with real worldactions. As an example, a sponsored virtual element may be at a virtuallocation that corresponds to the real-world location of a sponsor'sstore, restaurant, outlet, etc. If a player makes a purchase, enters acode made available at the real-world location, or takes another actionat the real-world location action meeting specified criteria, a specialvirtual experience may be made available to the player in theparallel-reality game.

The chat room module 330 determines chat room locations in the virtualworld based on player locations. The chat room locations may correspondto points of interest in the real world. The chat room module 330analyzes the player locations gathered from client devices 120 in theuniversal game module 310 and uses a clustering and border adjustmentmethod to identify groups of players that each correspond to ageographic area. The chat room module 330 may identify a point ofinterest in each geographic area as a chat room location based on thedata about players in that area (e.g., by comparing a centroid of theplayer locations to the locations of points of interest or by analyzingthe frequency or amount if interaction between players and virtualelements located at points of interest, etc.). The chat room module 330may update the chat room locations periodically (e.g., daily, weekly,monthly, etc.) or when triggered by a provider via the game server 110.The chat room module 330 provides the chat room locations to theuniversal game module 310, which includes the chat rooms in the totalgame state, and provides messages between users of the chat rooms.

In various embodiments, the chat room module 330 performs iterativek-means clustering before iterative border adjustment to determine thechat room locations. Using k-means clustering alone may result in somecentroids that correspond to much larger numbers of players than others.For example, chat rooms in high density regions (e.g., within cities)may have large numbers of players assigned to them, resulting in crowdedchat rooms in which conversation moves too rapidly for players to easilyfollow. Conversely, chat rooms in low density regions (e.g., ruralareas) may include relatively few players and players may becomefrustrated with the lack of interaction. The border adjustment countersthis by bringing the number of players associated with each chat roomcloser to being equal. The chat rooms may remain at the determined chatroom locations in the virtual world until the game server 110 triggersthe chat room module 330 to update the chat room locations (e.g., when acertain period of time has passed).

Generally, to determine chat room locations, the chat room module 330accesses player locations for a geographic region (e.g., from the gamedatabase 330). The player locations may be represented as points on amap, where the map is a two-dimensional representation of the physicalworld. The chat room module 330 groups player locations into aggregatedpoints on the map.

In one embodiment, to group the player locations, the chat room module330 breaks the map into a multitude of cells (e.g., S-cells) coveringportions of the geographic area. The cells are geometric shapes thatdivide up the geographic region. The size of the cells may be determinedvia input from a provider or based on the contents or user population ofthe geographic region. The chat room module 330 assigns each playerlocation to a cell on the map and creates a singular point (referred toas a “aggregated point”) for each cell, and the chat room module 330weights the aggregated points by the number of player locations assignedto that particular cell. Generally, the point weight increases with thenumber of players associated with that aggregated point. For example, anaggregated point for a cell with twenty player locations assigned to itmay have a higher point weight than an aggregated point for a cell withonly three player locations assigned to it. The point weight may be thenumber of players associated with an aggregated point (i.e., theaggregated points of the previous example would have point weights oftwenty and three, respectively) or some other function of the number ofplayers. The chat room module 330 also assigns the aggregated point to alocation in the geographic region corresponding to the cell (e.g., themiddle of the cell or the mean of the player locations represented bythe aggregated point). Thus, an aggregated point represents one or moreusers located within the cell associated with the aggregated point.

The chat room module 330 uses iterative clustering on the aggregatedpoints to determine centroids based on distance between the centroidsand the corresponding aggregated points. For convenience, thisspecification describes k-means clustering a uses the term “iterativek-means clustering.” However, other clustering algorithms may be used.

To begin iterative k-means clustering, the chat room module 330 randomlyselects a number of locations in the geographic region to be centroids.In some embodiments, the chat room module 330 selects the number oflocations using a random grid generator or k-means++ initialization. Aprovider may specify, via the game server 110, the number of centroidsfor the chat room module 330 to use or the chat room module 330 maydetermine the number of centroids to use based on the number of weightedaggregated points for the geographic region. The chat room module 330assigns each aggregated point to the nearest centroid. The aggregatedpoints assigned to a centroid define a centroid area. For example,geographic area made up from all of the S-cells corresponding to theaggregated points assigned to the centroid. The chat room module 330determines the mean location of the assigned aggregated points for eachcentroid area and updates the centroids to be at the corresponding meanlocations. The chat room location module 330 iterates this process usingthe updated centroids until one or more completion criteria are met.

The chat room module 330 can employ multiple different completioncriteria for iterating using k-means clustering. In one embodiment, thechat room module 330 finishes iterating when none of the aggregatedpoints move from one centroid area to another between one iteration andthe next. In other embodiments, the completion criteria are met when theaverage distance from each aggregated point to its centroid is less thana threshold value or a specified number of iterations have beencompleted.

The chat room module 330 performs iterative border adjustment to modifythe centroid areas determined using k-mean clustering. Using thecentroid areas generated from the final iteration of the iterativek-means clustering, the chat room module 330 determines the clusterweight of each centroid area based on the point weights of its assignedaggregated points. In one embodiment, the cluster weight for a centroidarea is the cumulative number of players associated with it. Forexample, a centroid area may be assigned three aggregated points, whichhave ten, seventeen, and five player locations associated with them,respectively. Therefore, the cluster weight would be thirty-two.

The chat room module 330 reassigns aggregated points between centroidsto more closely balance the cluster weights of the centroids. The chatroom module 330 determines how to reassign aggregated points for eachiteration of the iterative border adjustment based on one or moreconditions. In one embodiment, the chat room module 330 reassignsaggregated points if a pair of centroids includes a source centroid anda sink centroid and the source centroid has a centroid area larger thana minimum size. A centroid is a source centroid if its cluster weight(representing the number of player locations associated with thecentroid) is higher than the average (e.g., mean) cluster weight of allthe centroids and a sink centroid if its cluster weight is lower thanthe average (e.g., mean) cluster weight of all the centroids. In otherembodiments, a centroid is a source centroid if the cluster weight isabove a maximum threshold and a sink centroid if the cluster weight isbelow a minimum threshold. These thresholds may be set numbers given bya provider or may be a certain percentage of the player population.These conditions help prevent the chat room module 330 from movingplayers from high cluster weight centroid to low cluster weightcentroid, thereby balancing the effects of the player locations on thedetermined chat room locations. Based on the conditions, the chat roommodule 330 determines a set of aggregated points to move betweencentroids, calculates a moving cost of moving the aggregated points, andmoves the aggregated points with the lowest moving cost.

For each iteration of the iterative border adjustment, the chat roommodule 330 finds neighboring centroid pairs where one centroid is asource centroid and the other centroid is a sink centroid and thecentroid areas are directly adjacent to one another in the geographicregion. For each neighboring centroid pair, the chat room module 330determines if the source centroid is above a minimum size. The size ofthe source centroid may be the physical size of the corresponding areain the geographic region, the cluster weight, or a combination of both(e.g., the area and weight must both be above corresponding thresholds).In some embodiments, the chat room module 330 only uses centroids withcentroid areas between a minimum and maximum area size for the centroidpairs to avoid creating chat rooms that are too close together in denseurban areas. For neighboring centroid pairs that satisfy theseconditions, the chat room module 330 identifies a set of aggregatedpoints to move from the source centroid to the sink centroid of theneighboring centroid pair and calculates the moving cost of moving a setof aggregated points from the source centroid to the sink centroid.

The moving cost is a function of the increase in the average distancebetween each aggregated point and the source centroid if the aggregatedpoints are reassigned to the sink centroid. For example, aggregatedpoints closer to the border between the two centroid areas of a centroidpair would have a lower moving cost than aggregated points near thecenter of the centroid area of a source centroid. In some embodiments,the moving cost is based on the point weights of the aggregated points.The chat room module 330 moves the aggregated points between centroidsof a neighboring centroid pair with the lowest moving cost, provided themoving cost is below a threshold moving value, and makes one move periteration of the iterative border adjustment. In further embodiments,the chat room module 330 moves multiple sets of aggregated points periteration.

In some embodiments, the chat room module 330 checks if moving the setof aggregated points satisfies a moving cost threshold. The chat roommodule 330 determines the moving cost of the set of aggregated pointsand if the moving cost is above the moving cost threshold (i.e., theaverage distance has increased too much), the chat room module 330 doesnot reassign the set of aggregated points. Otherwise, the chat roommodule 330 reassigns the set of aggregated points. The moving costthreshold may be determined by the provider or may be determined basedon the population of players within the geographic region, among othermethods.

The chat room module 330 determines new centroids from the means of thecentroids with their new assigned aggregated points, as was done withiterative k-means clustering. The chat room module 330 iterates throughthe steps of determining cluster weights of the centroids, reassigningaggregated points, and determining new centroids until a set of criteriaare met. These criteria may include there being no neighboring centroidpairs with both a source centroid and a sink centroid, no sourcecentroids above a minimum area size, no source centroids above a minimumcluster weight, no valid centroid pairs for which the moving costs arebelow the threshold moving value. In further embodiments, the chat roommodule 330 finishes iterating through the iterative border adjustmentafter a fixed number of iterations, which may be entered by a provider.The chat room module 330 may also finish iterating once all centroidareas of the neighboring pairs contain a number of player locationsbetween a minimum and maximum threshold.

The chat room module 330 creates chat rooms in the virtual world for thegeographic areas corresponding to the centroids. The chat rooms may belocated at points of interest within the geographic area correspondingto a centroid. In various embodiments, the chat room module 330 placesone chat room corresponding to each centroid. For a given centroid, thechat room module 330 retrieves the locations of points of interestwithin the centroid area from the game database 340. In one embodiment,the chat room module 330 places the chat room for a centroid at thepoint of interest in the centroid area that is closest to the centroid.Alternatively, the chat room module 330 may locate the chat room at thepoint of interest in the centroid area with the highest amount of playerinteractions or the lowest average (e.g., mean) distance to the playerlocations corresponding to the centroid. In yet another embodiment, thechat room module 330 places the chat room at the centroid, such that thechat room is not necessarily located at or near a point of interest. Thechat room module 330 facilitates conversations between player at thechat room locations and stores information describing the chat roomlocations and the conversations in the game database 340.

The game database 340 includes one or more machine-readable mediaconfigured to store game data used in the location-based game to beserved or provided to client devices 120 over the network 130. The gamedata stored in the game database 340 can include: (1) data associatedwith the virtual world in the location-based game (e.g. imagery dataused to render the virtual world on a display device, geographiccoordinates of locations in the virtual world, etc.); (2) dataassociated with players of the location-based game (e.g. playerinformation, player experience level, player currency, player inventory,current player locations in the virtual world/real world, player energylevel, player preferences, team information, etc.); (3) data associatedwith game objectives (e.g. data associated with current game objectives,status of game objectives, past game objectives, future game objectives,desired game objectives, etc.); (4) data associated virtual elements inthe virtual world (e.g. positions of virtual elements, types of virtualelements, game objectives associated with virtual elements,corresponding actual world position information for virtual elements,behavior of virtual elements, relevance of virtual elements, etc.); (5)data associated with real world objects, landmarks, positions linked tovirtual world elements (e.g. location of real world objects/landmarks,description of real world objects/landmarks, relevance of virtualelements linked to real world objects, etc.); (6) game status (e.g.current number of players, current status of game objectives, playerleaderboard, etc.); (7) data associated with player actions/input (e.g.current player locations, past player locations, player moves, playerinput, player queries, player communications, etc.); (8) data associatedwith virtual experiences (e.g., locations of virtual experiences,players actions related to virtual experiences, virtual events such asraids, etc.); and (9) any other data used, related to, or obtainedduring implementation of the location-based game. The game data storedin the game database 340 can be populated either offline or in real timeby system administrators or by data received from players, such as fromone or more client devices 120 over the network 130.

The game database 340 may also store real-world conditions data. Thereal-world condition data may include the aggregate locations of playersin the real world; player actions associated with locations of culturalvalue or commercial value; map data providing the locations of roads,highways, and waterways; current and past locations of individualplayers; hazard data; weather data; event calendar data; activity datafor players (e.g., distance travelled, minutes exercised, etc.); andother suitable data. The real-world condition data can be collected orobtained from any suitable source. For example, the game database 340can be coupled to, include, or be part of a map database storing mapinformation, such as one or more map databases accessed by a mappingservice. As another example, the game server 110 can be coupled to oneor more external data sources or services that periodically providepopulation data, hazard data, weather data, event calendar data, or thelike.

Other modules beyond the modules shown in FIG. 3 can be used with thegame server 110. Any number of modules can be programmed or otherwiseconfigured to carry out the server-side functionality described herein.In addition, the various components on the server-side can berearranged. Other configurations will be apparent in light of thisdisclosure and the present disclosure is not intended to be limited toany particular configuration.

Chat Room Location Clustering Examples

FIGS. 4A-4B are an example of player locations grouped into aggregatedpoints within a geographic region, which are used to further determinecentroids, according to one embodiment. In FIG. 4A, a subset 400 of ageographic region contains 4 cells 410 with player locations 420scattered throughout the cells 410. Since each cell 410 has playerlocations 420 located within it, and each cell 410 is associated with anaggregated point 430. The aggregated points 430 are weighted by thenumber of player locations 420 in the cells 410. In this example, thepoint weight 440 is the number of player locations 420, such as 6 forthe top left cell 410 or 5 for the bottom right cell 410. FIG. 4B showsthe entire geographic region 450 of FIG. 4B, which includes a centroidarea 460 of a centroid 470 and the subset 400 of the geographic region450. The centroid area 460 only cover s a portion of the geographicregion 450. The centroid 470 is located within the centroid area 460based on the point weights 440 for each cell 410 within the centroidarea 460. In particular, the centroid 470 is located within the centroidarea 460 at a location with large point weights.

FIGS. 5A-5C illustrate centroids 500 throughout the process ofperforming iterative k-means clustering and iterative border adjustment,according to one embodiment. FIG. 5A shows initial set of centroids 500Arandomly generated by the chat room module 330 for a geographic region510. FIG. 5B shows the centroids 500B after the chat room module 330 hasperformed iterative k-means clustering. Here, the centroids 500B aremore concentrated to one region at the top right of the geographicregion 510. FIG. 5C shows the centroids after the chat room module 330has performed iterative border adjustment. Here, the centroid 500C aremore clustered in the top right corner of the geographic region 510 thanthe centroids 500B of FIG. 5B. This indicates that there is likely ahigh density of player locations 420 in that portion of the geographicregion 510.

FIG. 6 is an example of chat room locations 610 associated with pointsof interest 600 within a geographic region, according to one embodiment.The chat room locations may be located at points of interest 600, likechat room location 610A, or may be located within a portion of thegeographic region 510 with a dense amount of points of interest 600,like chat room location 610B. The chat room module 330 may determinechat room locations 610 based on the locations of the points of interest600, either through weighting centroids by number of interactions withpoints of interest in an associated aggregated point or cell or throughlocating a certain number of chat rooms at points of interest with ahigh amount of user activity.

Exemplary Flow Diagrams for Determining and Selecting Chat RoomLocations

FIG. 7 is a flowchart depicting a method for providing messages from achat room to a user, according to one embodiment. The game server 110retrieves 710 chat room locations and selects 720 a chat room for a userof the virtual reality game to join. In some embodiments, the gameserver 110 receives the location of the user and selects the chat roomlocated closest to the user. In other embodiments, the game server 110provides the user with multiple chat room options based on the user'scurrent location, desired path, virtual elements, other users the userhas an affinity for, or any other criteria. The game server 110 provides730 messages from the chat room to the user through the user interfacemodule 230 of the user's client device 120.

FIG. 8 is a flowchart depicting a method 710 for determining chat roomlocations, according to one embodiment. The game server 110 maydetermine the chat room locations via the chat room module 330, and insome embodiments the chat room module 330 employs a machine-learnedmodel to determine the chat room locations. The game server 110retrieves 810 player data from the game database 340 describing playerlocation information. In some embodiments, the same method 710 isperformed using other game data, such as point of interest locations.The game server clusters 820 player locations into aggregated points bybreaking up the geographic region for the chat room locations into cellsweighted by player locations. The game server 110 generates a set ofcentroids with assigned aggregated points and iteratively adjusts 830the centroids based on constraints, such as the distances of theaggregated points to the centroids and the cluster weights of thecentroids. In some embodiments, this is done through iterative k-meansclustering followed by iterative border adjustment. The game server 110iteratively adjusts the centroids until a set of criteria is met, suchas that no aggregated point moving between centroids between iterations.Additional criteria may include that there are no neighboring centroidpairs with both a source centroid and a sink centroid, no sourcecentroids above a minimum area size, no source centroids above a minimumcluster weight, no valid centroid pairs for which the moving costs arebelow the threshold moving value. In further embodiments, the gameserver 110 adjusts the cluster weights of each centroid such that thecluster weight of each centroid is as close to average for all of thecentroids as possible without increasing the average distance fromcentroid to assigned aggregated point by a threshold amount.

Finally, the game server 110 determines 840 the chat room locationsbased on the centroids after adjustment. In some embodiments, the gameserver 110 also retrieves locations of points of interest in the virtualreality game and places chat room locations at the point of interestlocations. Further, the game server may only place chat room locationsat point of interest locations with the highest numbers of userinteractions, according to another embodiment.

FIG. 9 is a flowchart depicting a method 820 for clustering playerlocations into aggregated points on a map, according to one embodiment.In this embodiment, the game server 110 assigns 910 each player locationto a cell. Cells are geometric shapes that divide up a geographic region(e.g., S-cells). The game server 110 creates 920 a singular point foreach cell, known as an aggregated point, which is associated with apoint weight and a location in the geographic region. The game server110 clusters 930 the aggregated points into centroids using a clusteringalgorithm (e.g., k-means clustering).

FIG. 10 is a block diagram illustrating an example computer suitable foruse in the network computing environment of FIG. 1, according to oneembodiment. Specifically, FIG. 10 shows a diagrammatic representation ofa machine in the example form of a computer system 1000. The computersystem 1000 can be used to execute instructions 1024 (e.g., program codeor software) for causing the machine to perform any one or more of themethodologies (or processes) described herein, including thoseassociated, and described, with the components (or modules) of a gameserver 110 or client device 120.

The machine may be a server computer, a client computer, a personalcomputer (PC), a tablet PC, a set-top box (STB), a smartphone, a networkrouter, switch or bridge, a cell phone tower, or any machine capable ofexecuting instructions 1024 (sequential or otherwise) that specifyactions to be taken by that machine. Further, while only a singlemachine is shown, the term “machine” shall also be taken to include anycollection of machines that individually or jointly execute instructions1024 to perform any of the disclosed methods.

The example computer system 1000 includes one or more processing units(generally one or more processors 1002). The processor 1002 is, forexample, a central processing unit (CPU), a graphics processing unit(GPU), a digital signal processor (DSP), a controller, a state machine,one or more application specific integrated circuits (ASICs), one ormore radio-frequency integrated circuits (RFICs), or any combination ofthese. Any reference to a processor 1002 may refer to a single processoror multiple processors. The computer system 1000 also includes a mainmemory 1004. The computer system may include a storage unit 1016. Theprocessor 1002, memory 1004, and storage unit 1016 communicate via a bus1008.

In addition, the computer system 1000 can include a static memory 1006,a display driver 1010 (e.g., to drive a plasma display panel (PDP), aliquid crystal display (LCD), or a projector). The computer system 1000may also include alphanumeric input device 1012 (e.g., a keyboard), acursor control device 1014 (e.g., a mouse, a trackball, a joystick, amotion sensor, or other pointing instrument), a signal generation device1018 (e.g., a speaker), and a network interface device 1020, which alsoare configured to communicate via the bus 1008.

The storage unit 1016 includes a machine-readable medium 1022 which maystore instructions 1024 (e.g., software) for performing any of themethods or functions described herein. The instructions 1024 may alsoreside, completely or partially, within the main memory 1004 or withinthe processor 1002 (e.g., within a processor's cache memory) duringexecution by the computer system 1000. The main memory 1004 and theprocessor 1002 also constitute machine-readable media. The instructions1024 may be transmitted or received over a network 130 via the networkinterface device 1020.

While the machine-readable medium 1022 is shown in an example embodimentto be a single medium, the term “machine-readable medium” should betaken to include a single medium or multiple media (e.g., a centralizedor distributed database, or associated caches and servers) able to storethe instructions 1024. The term “machine-readable medium” shall also betaken to include any medium that is capable of storing instructions 1024for execution by the machine and that cause the machine to perform anyone or more of the methods or functions disclosed herein. The term“machine-readable medium” includes, but is not limited to, datarepositories in the form of solid-state memories, optical media, andmagnetic media.

While the present subject matter has been described in detail withrespect to specific exemplary embodiments and methods thereof it will beappreciated that those skilled in the art, upon attaining anunderstanding of the foregoing may readily produce alterations to,variations of, and equivalents to such embodiments. Accordingly, thescope of the present disclosure is by way of example rather than by wayof limitation, and the subject disclosure does not preclude inclusion ofsuch modifications, variations or additions to the present subjectmatter as would be readily apparent to one of ordinary skill in the art.

Additional Considerations

Some portions of above description describe the embodiments in terms ofalgorithmic processes or operations. These algorithmic descriptions andrepresentations are commonly used by those skilled in the computing artsto convey the substance of their work effectively to others skilled inthe art. These operations, while described functionally,computationally, or logically, are understood to be implemented bycomputer programs comprising instructions for execution by a processoror equivalent electrical circuits, microcode, or the like. Furthermore,it has also proven convenient at times, to refer to these arrangementsof functional operations as modules, without loss of generality.

Reference to servers, databases, software applications, and othercomputer-based systems, as well as actions taken and information sent toand from such systems, are provided to illustrate various concepts. Oneof ordinary skill in the art will recognize that the inherentflexibility of computer-based systems allows for a great variety ofpossible configurations, combinations, and divisions of tasks andfunctionality between and among components. For instance, serverprocesses may be implemented using a single server or multiple serversworking in combination, databases and applications may be implemented ona single system or distributed across multiple systems, and distributedcomponents may operate sequentially or in parallel.

In situations in which the systems and methods access and analyzepersonal information about players, such as location information, theplayers may be provided with an opportunity to control whether programsor features collect the information. No such information or data iscollected or used until the player has been provided meaningful noticeof what information is to be collected and how the information is used.The information is not collected or used unless the player providesconsent, which can be revoked or modified by the player at any time.Thus, the player can have control over how information about the playeris collected and used by the application or system. In addition, certaininformation or data can be treated in one or more ways before it isstored or used, so that it is anonymized. For example, a player'sidentity may be treated so that no personally identifiable informationcan be determined for the player.

As used herein, any reference to “one embodiment” or “an embodiment”means that a particular element, feature, structure, or characteristicdescribed in connection with the embodiment is included in at least oneembodiment. The appearances of the phrase “in one embodiment” in variousplaces in the specification are not necessarily all referring to thesame embodiment. Similarly, use of “a” or “an” preceding an element orcomponent is done merely for convenience. This description should beunderstood to mean that one or more of the element or component ispresent unless it is obvious that it is meant otherwise.

Where values are described as “approximate” or “substantially” (or theirderivatives), such values should be construed as accurate +/−10% unlessanother meaning is apparent from the context. From example,“approximately ten” should be understood to mean “in a range from nineto eleven.”

As used herein, the terms “comprises,” “comprising,” “includes,”“including,” “has,” “having” or any other variation thereof, areintended to cover a non-exclusive inclusion. For example, a process,method, article, or apparatus that comprises a list of elements is notnecessarily limited to only those elements but may include otherelements not expressly listed or inherent to such process, method,article, or apparatus. Further, unless expressly stated to the contrary,“or” refers to an inclusive or and not to an exclusive or. For example,a condition A or B is satisfied by any one of the following: A is true(or present) and B is false (or not present), A is false (or notpresent) and B is true (or present), and both A and B are true (orpresent).

Upon reading this disclosure, those of skill in the art will appreciatestill additional alternative structural and functional designs for asystem and a process for using ad hoc neural networks to processtransactions. Thus, while particular embodiments and applications havebeen illustrated and described, it is to be understood that thedescribed subject matter is not limited to the precise construction andcomponents disclosed. The scope of protection should be limited only bythe following claims.

What is claimed is:
 1. A method comprising: retrieving locations forchat rooms, wherein the locations were determined by: retrieving playerdata for users of a mobile application, the player data describing userlocations; applying a clustering algorithm to form clusters of userlocations, each cluster assigned to a centroid; identifying geographicareas corresponding to the centroids; adjusting the geographic areasbased on the assigned user locations; updating the centroids based onthe adjusted geographic areas; and determining chat room locationswithin the geographic areas based on the centroids; selecting one of thechat rooms for a user; and providing messages associated with theselected chat room for display to the user.
 2. The method of claim 1,wherein the player data further describes interactions of users withpoints of interest within the mobile application and wherein clusteringthe user locations comprises: assigning each user location to a cell ona map; creating a single point for each cell having a cell location anda weight indicating a number of user locations assigned to the cell; andclustering the cell points into points on the map based the celllocations and weights.
 3. The method of claim 1, wherein determining thelocations for chat rooms is further based on points of interest withinthe mobile application.
 4. The method of claim 1, wherein a trainedmachine-learned model determines the locations of chat rooms.
 5. Themethod of claim 1, wherein selecting one of the chat rooms for the usercomprises: receiving a location of the user; and selecting a chat roomfor which the chat room location is closest to the user location.
 6. Themethod of claim 1, wherein selecting one of the chat rooms for the usercomprises: receiving a user location of the user; identifying apredetermined number of chat rooms for which the corresponding chat roomlocations are closest to the user location; and receiving a selection ofone of the plurality of chat rooms from a client device of the user. 7.The method of claim 1, wherein the cells are granular polygons thatdivide up a map, wherein the map is a two-dimensional representation ofthe physical world.
 8. The method of claim 1, wherein the centroids areiteratively adjusted such that average distance from each user locationto the nearest centroid is minimized.
 9. The method of claim 1, whereindetermining chat room locations within the geographic areas comprises:retrieving object locations corresponding to points of interest withinthe geographic areas; and placing chat rooms for geographic areas atobject locations nearest the corresponding centroids.
 10. The method ofclaim 1, wherein determining chat room locations within the geographicareas comprises: retrieving object locations corresponding to points ofinterest within the geographic areas; and for each geographic area:determining a plurality of object locations within the geographic areas;and placing the chat room at the object location with a highest numberof user interactions from the plurality of object locations.
 11. Anon-transitory computer-readable storage medium comprising instructionsexecutable by a processor, the instructions comprising: instructions forretrieving locations for chat rooms, wherein the locations weredetermined by: instructions for retrieving player data for users of amobile application, the player data describing user locations;instructions for clustering the user locations; instructions foradjusting the centroids based on constraints; instructions foridentifying geographic regions corresponding to the centroids; andinstructions for determining chat room locations within the geographicregions based on the user locations within the corresponding centroids;instructions for selecting one of the chat rooms for a user; andinstructions for providing messages associated with the selected chatroom for display to the user.
 12. The non-transitory computer-readablestorage medium of claim 11, wherein the player data further describesinteractions of users with points of interest within the mobileapplication and wherein the instructions for clustering the userlocations comprise: instructions for assigning each user location to acell on a map; instructions for creating a single point for each cellhaving a cell location and a weight indicating a number of userlocations assigned to the cell; and instructions for clustering the cellpoints into points on the map based the cell locations and weights. 13.The non-transitory computer-readable storage medium of claim 11, whereininstructions for determining the locations for chat rooms are furtherbased on points of interest within the mobile application.
 14. Thenon-transitory computer-readable storage medium of claim 11, wherein atrained machine-learned model determines the locations of chat rooms.15. The non-transitory computer-readable storage medium of claim 11,wherein the instructions for selecting one of the chat rooms for theuser comprise: receiving a location of the user; and selecting a chatroom for which the chat room location is closest to the user location.16. The non-transitory computer-readable storage medium of claim 11,wherein the instructions for selecting one of the chat rooms for theuser comprise: instructions for receiving a user location of the user;instructions for identifying a predetermined number of chat rooms forwhich the corresponding chat room locations are closest to the userlocation; and instructions for receiving a selection of one of theplurality of chat rooms from a client device of the user.
 17. Thenon-transitory computer-readable storage medium of claim 11, wherein thecells are granular polygons that divide up a map, wherein the map is atwo-dimensional representation of the physical world.
 18. Thenon-transitory computer-readable storage medium of claim 11, wherein thecentroids are iteratively adjusted such that average distance from eachuser location to the nearest centroid is minimized.
 19. Thenon-transitory computer-readable storage medium of claim 13, wherein theinstructions for determining locations for chat rooms further comprise:instructions for retrieving object locations corresponding to points ofinterest within the mobile application; and instructions for placingchat rooms for a location cluster at a nearest object location.
 20. Thenon-transitory computer-readable storage medium of claim 13, wherein theinstructions for determining locations for chat rooms further comprise:instructions for retrieving object locations corresponding to points ofinterest within the mobile application; and for each cluster:instructions for determining a plurality of object locations within ageographic region corresponding to the cluster; and instructions forplacing the chat room at the object location with a highest number ofuser interactions from the plurality of object locations.